Indirect social influence helps shaping the diffusion of innovations.

For understanding the diffusion of an innovation through a social group, we need to understand the way in which our own social interactions influence our decision taking. It is usually assumed that only direct interactions, those that form our social network, determine the dynamics of adopting innovations. To test this assumption, we performed experiments specifically designed to capture the influence that an individual receives from their direct social ties as well as from those socially close to them, as a function of the separation they have in their social network. The results of 21 experimental sessions with more than 590 participants show that the rate of adoption of an innovation is significantly influenced not only by our nearest neighbors but also by the second and third levels of influences an adopter has. In this talk we will present both the experimental setup as well as the mathematical model used to fit the results. We will explain the results obtained, namely, that innovation adoption is indeed a complex process in which an individual feels significant pressure not only from their direct ties but also by those socially close to them.